Note: The job is a remote job and is open to candidates in USA. Microsoft Security Studio seeks a software engineer to build AI-infused security solutions alongside customers. The role owns the end-to-end development and production delivery of secure software and agentic systems, and turns customer insights into reusable engineering assets and product improvements.
Responsibilities
- Design and build AI-infused security software with customers, including cloud services, intelligent applications, security automation, agents, developer tooling, integrations, and distributed systems
- Embed with customer engineering and security teams to understand desired outcomes, architecture, threat models, data, and operational constraints, then translate ambiguity into executable engineering plans
- Co-develop in short, iterative cycles, demonstrating working software and using real-user feedback, evaluations, telemetry, and operational data to refine the solution and measure success
- Own production-quality delivery from prototyping and architecture through implementation, automated testing, CI/CD, infrastructure as code, deployment, observability, troubleshooting, documentation, operational readiness, and handoff
- Use AI-assisted engineering across the lifecycle and build agentic systems that safely access enterprise data and tools, with appropriate human review, identity, authorization, data boundaries, isolation, auditability, guardrails, and accountability
- Apply secure-by-design and privacy-by-design principles, including threat modeling, least privilege, secrets and identity management, data protection, dependency and vulnerability management, and secure operations
- Convert customer-specific learning into reusable components, accelerators, reference implementations, engineering patterns, paved paths, and actionable product feedback
- Lead significant technical workstreams by setting direction, decomposing ambiguous problems, making architecture decisions, managing dependencies, risks, and trade-offs, and communicating clearly with technical and senior stakeholders
- Collaborate in small multidisciplinary teams, learn rapidly, experiment responsibly, challenge assumptions constructively, and share knowledge across engagements
Skills
- Bachelor's Degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in one or more languages such as C, C++, C#, Java, JavaScript, TypeScript, Go, Rust, or Python; **or equivalent experience**
- Demonstrated experience designing, building, testing, deploying, debugging, and operating substantial production software or cloud services
- Strong software-engineering fundamentals, including data structures, algorithms, APIs, distributed systems, cloud architecture, testing, reliability, and maintainable design
- Experience translating ambiguous, evolving customer or stakeholder needs into architecture, engineering plans, working software, and measurable outcomes
- Practical knowledge of secure software engineering, including authentication and authorization, identity, secrets management, threat modeling, data protection, secure dependencies, vulnerability remediation, and monitoring
- Ability to explain complex technical concepts, architecture decisions, trade-offs, and delivery risks to technical and nontechnical audiences
- Master's Degree in Computer Science or a related technical field and 6+ years of technical engineering experience; or Bachelor's Degree and 8+ years of technical engineering experience; **or equivalent experience**
- **Strong hands-on experience building and operating AI- or LLM-based applications, agents, or developer systems**, including orchestration, grounding/RAG, structured tool use, evaluation, observability, safety controls, and production monitoring
- Experience building **agentic systems that interact with enterprise data, APIs, tools, or workflows**, with attention to identity, authorization, auditability, data boundaries, and safe execution
- Experience using AI-assisted development and coding agents across the engineering lifecycle
- Experience building cybersecurity products or solutions in areas such as security operations, vulnerability management, identity, endpoint or cloud security, software supply-chain security, automation, or AI security
- Experience with cloud-native architecture, distributed systems, containers, infrastructure as code, CI/CD, observability, reliability engineering, and live-site operations
- Knowledge of **AI security and security for AI**, including prompt-injection defenses, sensitive-data handling, grounding controls, model or agent evaluation, responsible AI, and safe tool execution
- Demonstrated ability to move from **customer problem → prototype → production solution → reusable engineering asset** while balancing speed, quality, security, and maintainability
- Experience partnering with product engineering teams to turn customer scenarios and technical blockers into actionable requirements, prototypes, or validation evidence
- Ability to work effectively in small, high-ownership multidisciplinary teams and with senior customer engineering and security leaders while remaining deeply hands-on
Company Overview
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